Wonder, Play, Learn: How Might Students Wonder and Play Their Way into Deep Learning

How might we encourage students to "wonder" and “play” their way into deep learning? It is within the context of design education that I explore this question. Design students are expected to develop expertise in designing for wicked problems and long time horizon futures. This requires efficiencies with understanding and navigating complex systems, drawing productively upon vast information resources, agile prototyping skills and evaluative methods, and resilience in a highly iterative, low-­‐signal feedback environment. While experts thrive within the complexity of systems-­‐ level thinking, novices tend to become overwhelmed, looking to the experts for direction. Experts’ knowledge and processes tend to be tacit leaving novices floundering for productive courses of action. This thesis explores a framework for wonder (wonder as experience, interaction, action, sustained action) as a means to bridge this gap. Through this study of wonder, differences in organization of knowledge between experts and novices, aspects of motivation in game and learning environments, fly-­‐on-­‐the-­‐wall observations in a design studio classroom, and two sample participatory and user studies with masters and undergraduate students, this thesis puts forth that wonder provides a framework for: a.) unpacking expert processes thereby making these explicit/accessible to novices; b.) designing student-­‐centered learning with flexible scaffolding to address students’ motivational ebbs and flows as they develop expertise; c.) increasing agency by triggering the novice’s capacity for wonder and extending that through a frame that focuses attention and directs and sustains effort.